The Significance of Tree Height as a Predictor of Tree Mortality during Bark Beetle Outbreaks in a Small Catchment

Author:

Schmidt Susanne I.1ORCID,Fluksová Hana2,Grill Stanislav23,Kopáček Jiří4

Affiliation:

1. Department of Lake Research, Helmholtz Centre for Environmental Research, 39114 Magdeburg, Germany

2. Faculty of Science, University of South Bohemia, 37005 České Budějovice, Czech Republic

3. Department of Geoinformatics, Faculty of Science, Palacky University, 17. Listopadu 50, 77146 Olomouc, Czech Republic

4. Biology Centre CAS, Institute of Hydrobiology, Na Sádkách 7, 37005 České Budějovice, Czech Republic

Abstract

Bark beetle outbreaks damage forests and kill trees worldwide, but many aspects of their dynamics remain unexplained. Our aim was to identify predictors for individual tree deaths within the small (0.7 km2) Plešné Lake catchment in the Šumava National Park in southwestern Czechia. Within this area, >60,000 trees were geo-referenced and categorized from ten aerial images (20 cm spatial resolution) between 2000 and 2015. For each year for which aerial images were available, we calculated tree densities of different categories and diameters. Tree height was evaluated by means of LiDAR in two terrestrial campaigns (2010 and 2011). A machine learning technique was then used to evaluate the most important variables. The resulting relationships were largely nonlinear and differed among years; however, individual trait tree height proved to be the most influential variable in each year. Higher trees were more likely to have died during either the undisturbed phase (2000 and 2003), the disturbed phase (2005–2011), or the recovery phase (2013). Our results indicate that salvage logging may not be the most effective measure for protecting trees in small catchments.

Funder

EU Operational Programme Research, Development and Education

The Ministry of Education, Youth and Sports of the Czech Republic

Norway Grants

Czech Science Foundation

Publisher

MDPI AG

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3